Apple

Sr. Data Scientist, Subscriptions

SQL Python

July 17, 2022

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San Diego, CA, United States

July 17, 2022

Apply Now

Job description

Summary

Posted: Jul 15, 2022

Weekly Hours: 40

Role Number: 200400134

We're idealists. Inventors. Forever tinkering with products and processes, always on the lookout for better. Whether you work at our global offices, offsite, or even at home, a job at Apple will be demanding. But it also rewards forward-thinking, creative thinking and hard work. And none of us here would have it any other way. Does an exciting, dynamic, fast paced and pressure-filled environment catch your attention? Do you like puzzles and determining solutions that are not obvious? Terrific! Consider joining us. We are looking for experienced individual who will focus on exploratory analysis and development of innovative components to grow engagement of users, specifically in the areas of feature usage behavior and conversion optimization.

Key Qualifications

SQL, R or Python
5 years of industry experience
Consumer technology or a subscription based business is a plus
Experience with growth or product analytics is a plus
Ability to structure and solve problems
Communication skills to package findings
Work well within multi-functional teams

Description

This role focuses on subscription analytics and initiatives to drive growth. The tasks fall broadly into these areas: Work with engineering to identify data needs for new initiatives and make sure the data pipeline is built. Partner with instrumentation team to ensure tracking is in place before launches Identify, measure and communicate critical metrics for overall business and key initiatives. Build and maintain regular reports and provide ad-hoc analysis to support business needs Identify key takeaways from data and distill findings into recommendations for business owners Independently manage partner relationships with Engineering, Business, Product, Finance and other multi-functional teams within Apple

Education & Experience

Minimum of Bachelors degree (Masters preferred) in the fields of Information Science or Quantitative Disciplines - Statistics, Predictive Analytics, or Applied Mathematics.